Our goal of to reduce color variation internal rejections to less than 1.8%. We figured out that our blending of the colors process is not good enough. We have tried a few different blenders but nothing seems to work. We are again waiting for another blender to show up for us to see a demo.

How was the 1.8% determined? Logical analysis based on logical information and historical performance? Or more of a guesstimate?

Was there an action plan developed that supported at 1.8% goal achievement? Was it possible to see with each step in the action plan, what the result would be on the process? Did the action plan include resources appropriate to achieving the goal?

Who was involved in the goal and plan development? People familiar with the process?

Was it possible to determine, before this point, that the goal would not be achieved? Reporting metrics on a regular basis is one thing...I also like to show "on pace" for those metrics where I can see a potential problem in the making.

To be honest, not every goal is achieved by every organization. We can't predict the future and failure to achieve goal happens. But you're right in trying to figure out 'what now'. When an auditor came in, we wouldn't hide such "failures". Instead, we were honest about them, outlined how the results were presented, showed additional root cause analysis, demonstrated how we "re-spun" the PDCA cycle, and outlined the action plan for the immediate future.

Our goal of to reduce color variation internal rejections to less than 1.8%. We figured out that our blending of the colors process is not good enough. We have tried a few different blenders but nothing seems to work. We are again waiting for another blender to show up for us to see a demo.

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I don't know, but it sounds to me you're on top of it. Trying different blenders is no easy task.

Is that "Another blender" the correct attack for this issue ??
What is different in that blender than the few different blenders that you have tested out ?
If nothing significant, than the challenge is elsewhere.
What is your current internal rejection percentage, which you want to hit to 1.8 %
Its your company and your objective. You are free to reset your objective, based on data you have.
If the target of 1.8 % an error, admit it, and justify the new objective target.

1.8% rejection goal isn't unreasonable. this is a matter of physics and/or geometry and as such is totally solvable. in fact I would make a goal of no rejections.

Miner has the right question path: we must understand the varation first, then use that knowledge to determine the causal mechanism, then a solution will become apparent:

how do you measure color variation? Is it repeatable?
How do you sample each batch? one sample per batch or one sample every hour? or?
Do you reject the whole batch or parts of it?
What pattern is there to the variation? within batch, day to day, batch to batch?

Is the color variation within - batch, short term batch - 2 - batch, long term batch - 2 - batch?

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The color variation is within the batch. So a mixture of colorant is produced. It is fed into the extruder. The job may start off the correct color and very inconsistent - and then suddenly BOOM!! The feeder will feed in some of the mixture where there are clumps of colorant which were not blended evenly. The result is pellets that have a "salt & pepper" color - very light and dark.

Our customer's use very small extruders to process our material, so color consistency is a major key to them.

How was the 1.8% determined? Logical analysis based on logical information and historical performance? Or more of a guesstimate?

Was there an action plan developed that supported at 1.8% goal achievement? Was it possible to see with each step in the action plan, what the result would be on the process? Did the action plan include resources appropriate to achieving the goal?

Who was involved in the goal and plan development? People familiar with the process?

Was it possible to determine, before this point, that the goal would not be achieved? Reporting metrics on a regular basis is one thing...I also like to show "on pace" for those metrics where I can see a potential problem in the making.

To be honest, not every goal is achieved by every organization. We can't predict the future and failure to achieve goal happens. But you're right in trying to figure out 'what now'. When an auditor came in, we wouldn't hide such "failures". Instead, we were honest about them, outlined how the results were presented, showed additional root cause analysis, demonstrated how we "re-spun" the PDCA cycle, and outlined the action plan for the immediate future.

Click to expand...

The 1.8% percentage was determined by reviewing the rejections from 2014.

During our Management Council Meeting we reviewed the metrics and all of management, including process and production, decided that this was the major cause of our down-time and honestly we are losing money having to correct each one of these rejections. The correction method is taking the material and reprocessing it so re-blend the color.

In the previous years - we did not have such a problem with color variation. This was due to our customers giving us more freedom on what colorants we could use. As the FDA cracks down harder and harder, we are limited on the colorants we can use and unfortunately, a lot of the ones we can use can't be blended that easily. Most of the time now, our customers tell us the colorants we MUST use.

Is that "Another blender" the correct attack for this issue ??
What is different in that blender than the few different blenders that you have tested out ?
If nothing significant, than the challenge is elsewhere.
What is your current internal rejection percentage, which you want to hit to 1.8 %
Its your company and your objective. You are free to reset your objective, based on data you have.
If the target of 1.8 % an error, admit it, and justify the new objective target.

Click to expand...

It does seem to the blender in our eyes.

We have a larger blender that works great! But unfortunately, a lot of our feeder batches are too small for it to blend the mix correctly and evenly.

So we have been on the hunt for a smaller blender. The manufacturer of the large blender we have does not produce a smaller version.

1.8% rejection goal isn't unreasonable. this is a matter of physics and/or geometry and as such is totally solvable. in fact I would make a goal of no rejections.

Miner has the right question path: we must understand the varation first, then use that knowledge to determine the causal mechanism, then a solution will become apparent:

how do you measure color variation? Is it repeatable?
How do you sample each batch? one sample per batch or one sample every hour? or?
Do you reject the whole batch or parts of it?
What pattern is there to the variation? within batch, day to day, batch to batch?

Click to expand...

We measure the color variation visually. It is extremely noticeable even from a distance that the pellets are different shades of color.

The whole lot has to be rejected as the color variation comes on suddenly and without notice. By the time it is noticed, we have salt and pepper pellets mixed in the with the "good" pellets.

The color variation occurs batch to batch - it depends on the formulation and the amount of colorants in each. We have process concentrating on reviewing the formulas before they go out on the floor. Process is included to try to adjust the process by slowing the line down to help incorporate the "clumped" pockets of color, but process doesn't always work either.

We measure the color variation visually. It is extremely noticeable even from a distance that the pellets are different shades of color.

The whole lot has to be rejected as the color variation comes on suddenly and without notice. By the time it is noticed, we have salt and pepper pellets mixed in the with the "good" pellets.

The color variation occurs batch to batch - it depends on the formulation and the amount of colorants in each. We have process concentrating on reviewing the formulas before they go out on the floor. Process is included to try to adjust the process by slowing the line down to help incorporate the "clumped" pockets of color, but process doesn't always work either.

Click to expand...

Nikki,
Beverly has published some Measurement Systems Analysis in the Resource section. Some of them are very practical to use. We have the same situation but ours is Bright and clear or Hazy. We use attribute MSA to test the operators. This could also be a nice little six sigma project for you and your team. The goal is to improve profitability by reducing defect. There are consultants in this Forum that can help you out. Hope it helps.

The color variation is within the batch. So a mixture of colorant is produced. It is fed into the extruder. The job may start off the correct color and very inconsistent - and then suddenly BOOM!! The feeder will feed in some of the mixture where there are clumps of colorant which were not blended evenly. The result is pellets that have a "salt & pepper" color - very light and dark.

Our customer's use very small extruders to process our material, so color consistency is a major key to them.

Click to expand...

Since you said in another post that the color variation is visually apparent, I'll skip the recommendation for an MSA in this post. I would start by identifying all of the control variables available for the mixing process as well as all of the uncontrollable noise variables. If the number is small, you could start with a screening designed experiment to identify the factors with the greatest impact on the color variation. If the number of variables is high, you could prescreen some of them using a C/E Matrix or similar approach.

"the color variation usually occurs at the end of the job". this is a HUGE clue if true and not just anecdotal.
I think I hear you saying that when it occurs it occurs near the end of the batch, and it doesn't occur on every batch.
It would be a good exercise to draw out (on paper or whiteboard forget PowerPoint and visio, etc.) how the equipment actually does its job. Then think about how it can create these clumps. Then go out and observe the operation to catch it doing it. This may take some time, but not as much as you have already taken...

you might also want to check out my resource: A scientific approach to determining root cause. its introductory but it might give you some ideas.

"...Even if we go the next two months without an internal rejection, we still fail...."

Allow me just an elaboration on the unsaid side issue, as the experts here have given you plenty to work on for finding causes.

My first impression upon reading your post brought back ancient memories of when I worked in extrusion as well. Our company had quarterly goals for things like this including accidents, sales, output, etc. and if we met our goal there was a cash bonus at the end of the year.

One problem with this type of goal, when it is blown early, there is a terrible morale drop, especially if the goal is financially incentivized, which they sometimes are. For the remaining months a “what does it matter” attitude settles in, since nothing can repair the damage to a missed target, it is usually mathematically impossible.

While having measurable goals is great, they come with some negative effects. I have found it better in these cases to use the percentage number in a control chart, so instead of a term limited duration of time (quarterly), it is continuous data, and the number is simply taken, (like temperature), when needed.

This keeps everyone involved without feeling that “the next two months are wasted, we cannot hit the goal anyway”. Instead, using a moving number, improvement can immediately be applied and results seen without throwing out the next two months and then trying again.

Yes, I know there is no real difference quarterly-wise, the difference is in perception.

In the quarter, you have already lost, why improve? - In a “limitless” duration, the number can be affected immediately, so improvement is not “wasted”.

I know it is all semantics, but perception is everything, especially when more than a handful of people are involved.

I know it's not methodically sound to jump to "solutions" (before you know what the problem really is), but you already have a battery of analysis experts lined up here so I'll just add my 2 cents on the technological side.

Additive mixers tend to be a huge headache with small batch processes, especially with very potent colorants that are required in very low doses. One possible technological solution is to switch from pre-mixing to online dispensing. You need a very accurate dispenser for every additive, and they all feed directly into the extruder's hopper. It's an expensive solution but it provides great control. Might be worth it if you run lots of such small batches.

The fact that you get the variations near the end of the batch hints that this might have something to do with hopper dynamics. When the hopper is not full it changes and you might get segregation of the different ingredients due to their different physical properties. If this is the cause you just need to make some extra mixture so that you can have a full hopper all the way through.

One last thought is maybe you need a longer extruder, or another type of extruder / screw / barrel - one that mixes better and is thus less sensitive to the input material.